Journal of Construction Engineering and Management

Producing adequate lift plans for a transfer operation system (TOS) used in irregularly shaped high-rise building constructions is a more complex task than for an all-floor lift operation system. In the TOS, a resource whose destination floor is higher than the current zone must transfer to one of the lifts of the upper zone at the transfer area after passing through the current zone. This transfer process requires waiting time at the transfer area, which is repeated until the resource arrives at its destination floor. However, the current lift planning method for the TOS considers each zone to be completely independent, which underestimates the required number of lifts and results in the late delivery of resources to the work floors. Therefore, this study proposes a simulation-based lift planning model for the TOS. The proposed model helps a lift planner to find an optimal lift plan for the TOS with the lowest cost while satisfying the constraints of the total lifting time and average journey time within a short planning time. Furthermore, the proposed model contributes to successful project completion by transporting resources to work floors in a timely manner.

Setting the baseline labor productivity (BP) values for construction activities is essential to compare the productivity performances of projects or contractors. The BP value can also be used to estimate the costs incurred due to the loss of productivity on a certain project. The objective of this research is to develop a Monte Carlo simulation-based baseline labor productivity model (MCBPM) that can be used to determine the BP value for formwork operations. After proposing a framework for the MCBPM, empirical data regarding the labor productivity of timber formwork for several building structures were collected from 40 contractors in Ethiopia. Thereafter, a Monte Carlo simulation was carried out to simulate the formwork labor productivity, and BP values were set. Following the simulation, the BP values for column, beam, slab, and wall formworks, at 95% probability, were found to be 0.94, 0.80, 0.93, and $1.0{\mathrm{m}}^2/\mathrm{h}$, respectively. Compared to the previous BP models, the MCBPM provides more reliable estimation accuracy and efficiency to set the BP value based on the confidence level. This study contributes to the body of knowledge by proposing a stochastic labor productivity model that can be used as a practical tool in construction projects to forecast the BP values at certain confidence levels.

This paper presents the results of a study to compare the performance of design-bid-build (DBB), construction manager at risk (CMR), and design-build (DB) project delivery systems in the US building construction industry. By leveraging verified data from 212 projects, a best subset analysis was used to generate regression models that explain the greatest amount of variance in five measures of project performance: unit cost, cost growth, schedule growth, construction speed, and delivery speed. From these regression models, the average of the predicted project performance was calculated for each delivery system when holding all other variables constant. The results show that, on average, projects with a DB delivery system are delivered faster and with lower cost and schedule growth than projects structured as CMR or DBB. In addition, the completed unit cost of DB projects is comparable to DBB and slightly less than CMR projects. These results are generally consistent with findings from seminal articles published in the late 1990s, as well as more recent works that also compared performance across delivery systems. However, the modeling does indicate that, except for delivery speed, the gap in performance between DBB, CMR, and DB has narrowed over time. This research provides an updated benchmark for the performance of the most commonly used project delivery systems, which has value to owners seeking guidance when making strategic decisions in structuring their projects.

Prior research has disagreed on the definition of construction project success and the best way to achieve it. Additionally, there is very little research that takes a practitioner’s viewpoint and provides findings useful to project managers in their day-to-day dealings. To fill this gap, the following research was conducted to determine the social mechanisms used by project managers and project teams to achieve success. The research includes an in-depth literature review, along with a two-part qualitative study consisting of thirty semistructured interviews with current or former construction project managers. Focusing on project personnel and communication as the key ingredients, a model of antecedents and causal social mechanisms is developed. The constructs, or antecedents, to personnel are planning, choosing, and retaining. The constructs, or antecedents, to communication are frequency, understanding, and inclusivity. The causal social mechanisms that lead from the antecedents to success are described in detail and benefit practitioners because they provide both the novice and the experienced construction project manager with insights into the “how” and not just the “what” of previously identified critical success factors.

Defects pose considerable risks to construction projects in terms of both cost and quality, and identifying defects thus is crucial to effective construction quality management. In this study, data for 45 cases were obtained from the Public Construction Management Information System (PCMIS) of Taiwan. A combined machine learning method comprising association rule mining and a Bayesian network was employed to identify the relationships between defects as well as their occurrence probabilities. A total of 33 association rules and 11 high-risk defects were detected. The Swiss cheese model (SCM) was used to formulate four defensive layers and analyze the high-probability, strong-correlation, and multipath characteristics of high-risk defects. Specifically, the defect quality control inspection not implemented had the highest risk values. In the correlation analysis, more high-risk defects meant reduced inspection scores and construction quality; risk values and inspection scores had a strong negative correlation ($r=-0.85$). This study proposes innovative hybrid machine learning to evaluate the risks of defects, and the SCM was implemented to establish the risk factors and hierarchical relationships of the defects to determine their priority order in management. Future studies should analyze the time series of defects and employ sequential data to forecast their order of occurrence and relationships at different times, thereby increasing the understanding of dynamic construction projects.

Stakeholder conflicts are hard to avoid in the implementation of megaprojects due to the diverse interests and aims among stakeholders. The previous study does not provide much evidence on dynamic patterns of stakeholder conflicts in the project duration from the planning to the construction and handover stage. Therefore, this study established a network-based framework to analyze the dynamics of stakeholder conflicts by detecting the critical conflicts and the affected relationships among stakeholders with a 16-year case study of the Hong Kong-Zhuhai-Macao Bridge project. Finally, a stakeholder-conflict map was proposed to provide management strategies considering the conflict criticalness and stakeholder participation of each stakeholder conflict. After reviewing 1,748 official documents from 2003 to 2018, the chronological features of environmental conflicts, neighboring conflicts, and traditional conflicts are detected. The changes of stakeholder relationships in the project duration are discussed by five stakeholder groups: local industry, green group, supervision group, construction group, and governmental organizations. The Mirror Z strategies of stakeholder conflicts are proposed in the phases of planning, construction, and handover, respectively.

When a project activity has already started, tracking information such as percentage complete and current activity duration and cost can be easily retrieved. This information can be used to update the project schedule to anticipate the eventual project duration and cost more precisely. But hardly any studies analyzed how more accurate or reliable activity tracking information can be compared with the initial (planned) estimates, let alone which mathematical forecasting expressions are the most accurate. This paper quantified forecasting accuracy by extracting over 3,000 activities with partial tracking information (i.e., those which have already started but are not yet complete) from a real project data set. Two expressions for forecasting the activity duration and cost were tested by comparing their performance with initial (planned) and final (actual) values. The contributions to the body of knowledge are fourfold. First, it was shown that activity tracking information considerably outperforms planned estimates. Second, using two expressions can significantly minimize the deviations of time and cost estimates. Third, remaining activities’ duration and cost estimates can be closely modeled with log-normal distributions as a function of the activities’ percentage complete. Fourth, variability decreases linearly as activities approach their end. These findings allow project managers to better anticipate and model the duration and cost variability of ongoing activities and to improve the forecasting accuracy of the project duration and cost estimates.

Generating an object-oriented, geometric digital twin of an existing railway from its point cloud data (PCD) is a laborious task, needing 10 times more labor hours than scanning the physical asset. The resulting modeling cost counteracts the expected benefits of the twin. This cost and effort can be reduced by automating the process of creating such models. The first perceived challenge to achieving such automation is detecting masts from airborne light detection and ranging (LiDAR) data because their position and function (separating substructure from superstructure) is critical to the subsequent detection of other elements. This paper presents a method that tackles the aforementioned challenge by leveraging the highly regulated and standardized nature of railways. In railway infrastructure, the geometric relations of a unit contain overhead line equipment (OLE) between two mast pairs are consistent and repetitive throughout the track. The proposed method starts with tools for cleaning the PCD and roughly detecting its positioning and orientation. The resulting data sets are then processed by restricting the search region of the masts considering its positions compared with the track centerline. Subsequently, the masts are detected using the Random Sample Consensus (RANSAC) algorithm. The final deliverables of the method include the coordinates of the mast positions, detected point clusters and three-dimensional (3D) models of the masts in Industry Foundation Classes (IFC) format. The method was implemented in a prototype and tested on three railway PCDs with a cumulative length of 18 km. The results indicated that the method achieves an overall detection rate of 94%. This is the first method in automatically detecting masts from airborne LiDAR data.

Rework is positively linked with increased safety risks. As a precursor to decreased rework and enhanced safety performance, this study appraised the correlative causes of rework and safety incidents. To do this, 20 rework causes that undermine safety performance were first identified through the literature review. Using a survey questionnaire involving Malaysian construction professionals (owners, consultants, and contractors), the causes were prioritized based on frequency, severity, and importance indices. The five leading rework-safety causes were ranked as follows: poor coordination, insufficient communication, poor subcontractor management, improper supervision and inspection, and poor site management. Spearman’s rank correlation tests revealed a significant agreement between the respondent groups. An exploratory factor analysis identified the five major underlying causal dimensions of rework and safety incidents to relate to the substandard management of equipment and machinery, poor project management practices, inherent dangerous, dirty, and difficult (3D) characteristics, improper production planning and work pressure, and inadequate personnel competency and knowledge. This paper bridges the identified knowledge gap concerning the dimensionality of rework and accident causation in construction, and the findings provide guidance for devising preventive measures for simultaneously addressing rework and safety problems.

Vital services like clean water, sewer, and electricity utilize underground infrastructure. Unfortunately, many damages to underground utilities are happening during the course of construction activities. Therefore, there is a need for a greater understanding of damage causes to better manage risks to underground utilities during construction work. Understanding the root causes will help stakeholders and policymakers make the best possible decisions to reduce future damages. In this study, utility locators’ perspectives regarding the damage causes and overall prevention process were collected, analyzed, and compared to excavators’ perspectives and responses that were previously reported. Surprisingly, the results suggest that stakeholders’ behaviors (i.e., human factor), rather than technology limitations or current policies, significantly contribute to a breakdown of the damage prevention process. Specifically, communication between stakeholders, excavators’ behaviors, and locators’ working conditions have been identified as crucial factors in the damage prevention process. There are few, if any, empirical studies that have recognized the human factor as a contributing element to utility damages. Thus, the findings will help improve future policy development. In addition, the clear and detailed description of damage causes and prevention processes will help stakeholders understand the contribution of their behaviors to the damage prevention process, which will result in a more reliable and workable process.

Although most safety guidelines and standards put hazard recognition as the first step of risk management, researchers found that only 6.7% of construction foremen could identify all the site hazards. Regarding construction safety and training, much research has shown that lack of hazard recognition could be attributed to familiarity with the task and being desensitized to the associated risks. The primary objective of this research was to assess hazard recognition and safety risk perception skills in the electrician trade among electricians in unions. Journeymen and apprentices were given photos of leading hazards in this trade. Each individual was asked to find hazards in the photographs and, once they were finished, they were asked to assess the risk associated with each photo. Hazard recognition and risk perception results were compared with those of subject matter experts. The results showed that both apprentices and journeymen were unable to identify an acceptable number of hazards when benchmarked to the experts’ expectations. The results also showed that journeymen were unable to perceive risks, compared with subject matter experts’ expectations. The primary contribution to the body of knowledge is the establishment of an evaluation process of hazard recognition and risk perception, as well as demonstration of the gap in outcomes of safety training programs. With the findings of this effort, electrical unions can understand existing hazard recognition and risk perception abilities and gaps of their apprentices and journeymen.

Construction and civil engineering professionals are recognizing a growing need for increased professional development, namely, leadership development, within the industry. However, many academic and workforce professions lack a clear definition of leadership that aligns with construction and civil engineering industry environments. To initiate the development of this definition and enhance the preparation and training of emerging industry professionals, this study utilizes the Delphi method to gain consensus from construction industry executives regarding necessary leadership competencies for workforce entry. The findings identified 24 leadership competencies that highlight the importance of both intrapersonal and interpersonal competencies that contribute to ongoing leadership conversations in the construction industry. A comparison of these competencies with the body of knowledge revealed leadership as consisting of both professional and technical competencies, shifting conceptualizations of leadership from a professional competency acquired through experience to an integrated competency that can be operationalized and taught in both technical and professional learning contexts.

Labor productivity in construction has fallen behind other industries in most of the world and has declined continuously for decades in the United States. To change this, the construction industry needs to know where to focus. This research aims to show how important craftsmen efficiency is for national construction labor productivity (CLP) development. Statistical analysis was used to compare craftsmen efficiency and CLP data from North America (NA) in the period 1972–2010. Craftsmen efficiency data were extracted from published work that measured direct work (DW) through work sampling, and CLP data were extracted from national databases. A statistically significant relationship between DW and CLP was established. This revealed that adding 36 s of DW to every work hour could yield a yearly return of 5.4 billion USD to the NA gross domestic product (GDP). Results show that more focus on activity and project level efficiency is crucial for changing the trends of national CLP. Industry leaders and policy makers now have a solid foundation for taking corrective actions for an industry plagued by low productivity.

The need to meet increasing economic vitality has caused continued deterioration of road surfaces owing to the constant use fueled by high traffic volume. Nighttime paving operations are often seen as a viable solution to reduce traffic disruptions due to maintenance and construction activities. However, state highway agencies (SHAs) are uncertain as to whether the quality of nighttime paving is at the same level of daytime paving. Although percent within limits (PWL) has shown great promise as a quality-based pay factor tool, limited empirical research exists that focuses on using this process as a postconstruction pay tool. The goal of this study is to assess the impact of nighttime and daytime paving on pavement quality using PWL. To achieve the goal of this study, data extracted from a review of existing literature and archival studies were analyzed using multiple statistical tools. This study examines rideability quality for 86 different projects from both nighttime and daytime asphalt paving projects over a 2-year period in South Carolina. It was found that nighttime projects were awarded more rideability bonus payouts while daytime projects were awarded more 100% rideability payouts. This study fills a gap in knowledge and practices by providing relevant information required to use PWL as a tool for measuring, enhancing, and optimizing quality or asphalt pavement. SHAs should consider including PWL in highway contracts as a tool for assessing the quality of projects.

A number of parallel lifting operations may take place simultaneously on a prefabricated construction site, likely resulting in workspace overlapping, which is likely to delay the project and even cause accidents. This indicates that the workspace is becoming a deficient resource, which needs to be addressed in project scheduling. To identify the workspace conflict, a 4D conflict detection approach was proposed in this study. First, the allocation of entity space, safety working space, and efficient working space were differentiated based on the characteristics of the prefabricated construction project, followed by analysis of the impacts of three kinds of space interference. Consequently, a workspace generation framework was established that considered both the motion of construction machinery and the requirement of laborers, and then the severity evaluation formula was established accordingly. Based on that, a hybrid axis-aligned bounding box (AABB) and orientational bounding box (OBB) algorithm was proposed to detect workspace conflicts. Finally, workspace conflict detecting and evaluating modules were implemented using Navisworks SDK. Empirical results showed that this algorithm is able to forecast the time–space conflicts accurately for prefabricated construction projects. Benefiting from the framework proposed in this research, project managers can detect workspace conflicts in advance and optimize the schedule to avoid schedule delays and extra cost, as well as to improve safety.

This study analyzes the cost performance of design-build (DB) and design-bid-build (DBB) delivery systems to examine whether one project delivery system (PDS) is always superior to the other when it presents lower cost growth. Previous studies have not yet separated the effects of PDS and third factors on cost performance and have thus been unable to determine the most significant factor affecting cost performance in the comparison of DB and DBB. Bidding characteristics tend to increase project costs during the construction phase and have been recognized as the third factors associated with the PDS and cost performance. The current study employed a causal relationship model, using path analysis to distinguish the effect of the PDS and bidding characteristics on cost performance, to identify the third factors as mediators and to determine whether the mediation effect of bidding characteristics has a statistically significant effect on cost growth. Subsequently, it applied a $t$-test to compare the cost performance of DB and DBB delivery systems across project types, based on 197 public projects in Seoul, South Korea. The results show that the cost performance of DBB has a mediation effect on architectural building projects but not civil infrastructure projects. It indicates a condition wherein DB should not be considered superior to DBB despite the lower cost growth. Thus, PDS have the potential to be misjudged when their cost-effectiveness is mediated by bidding characteristics. This study contributes to the construction engineering and management body of knowledge by providing a causal relationship analysis to compare DB and DBB cost performance based on a mediation effect. The findings from the study may guide practitioners in the architecture, engineering, and construction (AEC) industry to evaluate and select the appropriate PDS for specific project types and provide a method to benchmark DB against DBB.

Prefabricated construction (PC) is considered to be a low-carbon construction method in most cases, and PC technology drives advances in PC. The interorganizational diffusion of PC technology transcends organizational boundaries to achieve resource sharing, which transforms technology from theory to practice and from innovation to economic benefits. Existing research mainly focuses on developing and applying PC technology but ignores its interorganizational diffusion process. Understanding the interorganizational diffusion of PC technology is important for government policymaking. This paper looks at how PC technology is diffused among PC companies. A two-stage evolution framework was proposed based on social network theory. Using China’s PC-related cooperative patent data, macro diffusion characteristics and micro partner selection mechanisms underpinning its evolution were explored. The results revealed the scale-free feature of the interorganizational diffusion of PC technology and provided preferred collaborators for PC companies. This study advances theoretical systems of both PC and technology diffusion and can assist government and PC companies in improving diffusion performance.

Large-scale construction projects that unify multiple subprojects and cover a large site area have been increased by rapid urbanization. Frequent traffic accidents have occurred inside these construction sites, which highly requires a reasonable road system to prevent traffic problems from the planning level. To address the research gap in modeling road layout for large-scale construction projects, this paper develops a hierarchical road layout method. Specifically, the method is established in three levels to distinguish the traffic demands inside and outside subprojects. Permanent roads are reconstructed to form a basic road network for the three road levels. Two optimization models are established to arrange nodes and links on the basic network. Preliminary evaluation results of a tourist resort project show that the proposed method can improve efficiency and safety performance. Further, the scenario analysis proves the feasibility in other types of large-scale projects. This primary investigation initially considers road hierarchy and utilization of permanent roads. Hopefully, it will enhance the traffic performance of large-scale projects and inspire more concerns on the traffic planning at preconstruction stage.

The construction industry has strived for higher productivity in the last several decades, which has resulted in innovations and improvements, including methodologies, tools, and machines. By moving work from on-site to off-site, the objective is to use the workforce and machinery in a controlled environment without external interference for higher productivity and quality. However, the construction manufacturing domain may not benefit fully from modular construction and lean implementation when employing the stick-built under a roof method, which follows a similar construction process as the conventional on-site construction approach. This paper introduces a process-oriented framework which integrates value stream mapping (VSM) with a production line breakdown structure (PBS) to analyze current production line performance using key performance indicators (KPIs), assess the proposed solution for improved performance, and visualize the future implementation of the proposed solution on a construction manufacturing production line.

Many researchers, as well as industry practitioners, believe that offsite construction methods are associated with a lower level of worker safety risks than traditional onsite construction methods. This study aims to test such belief by comparing the list of worker safety risks identified by site supervisors for both onsite and offsite construction scenarios for the same building components. Specifically, Safe Work Method Statements (SWMS)—prejob hazard assessments required by law in Australia—were collected from two projects where offsite manufacturing has been used, and they were used as a basis for the investigation. Additionally, interviews were conducted with the site supervisors who developed the Statements for a more in-depth investigation of the worker safety risks involved with onsite and offsite construction methods, respectively. The analysis reveals that the total risk score (the higher the score, the more numerous the safety risks) would decrease in the offsite construction scenarios in each case, mainly due to significantly fewer work-at-height tasks included in the offsite construction scenarios. This study contributes to the body of knowledge by providing an empirical, evidence-based explanation for why offsite construction can help reduce safety risks on construction sites.

An effective material management system is key to the success of construction projects. However, the Indian construction industry suffers from many material management issues that lead to ineffectiveness in the material management system. Previous studies in the field have not comprehensively examined the issues affecting the schedule and cost performance of construction projects. To address this gap, this study identified a total of 33 material management issues from the existing literature and conducted interviews with 15 material management experts with more than $10\mathrm{years}$ of experience in material management. The data were collected through the use of a questionnaire survey completed by 86 procurement professionals. The results revealed six factors with a significant positive influence on the disruption of projects’ schedule and cost performances. Improper delivery of materials is the most critical material management factor, followed by inadequate planning of materials, lack of information and communication, financial issues in procurement, changes in scope of materials, and difficulty in transportation. The findings of this study enable construction practitioners to effectively focus on the few critical factors to improve the material management system and thereby enhancing projects’ schedule and cost performances.

There exists a plethora of studies that have examined the nature of rework in construction, yet it remains a problem in practice. It is proffered that the prevailing lens of error prevention that pervades practice has thwarted the ability of construction organizations to understand the context of rework causation and therefore learn from its occurrence. In this paper, a conceptualization of rework based on the manifestation of errors and violations is presented. The proposed frame of reference provides both researchers and construction organizations with a frame of reference to better understand the characteristics of rework causation. Corollaries from acquiring this understanding will be the ability to develop effective strategies to contain and reduce the manifestation of rework.